ALBERT

Description: Two methods for assimilating radar reflectivity into the COSMO numerical weather prediction (NWP) model were compared to precipitation forecasts. The first method assimilated observed radar reflectivity, and the second one assimilated observed and extrapolated radar reflectivity. The assimilation technique was based on the correction of the model's water vapour mixing ratio. The extrapolation was performed by the COTREC method and was 1 hour long. The model's horizontal resolution was 2.8 km. The comparison of methods was based on verification of the observed and forecast hourly precipitation. The comparison was performed for the 1 st , 2 nd and 3 rd hours of each forecast. On the whole, 45 forecasts from nine days of convective precipitation were evaluated for each hour. The evaluation included subjective verification and the following objective skill scores: Fractions Skill Scores, SAL and a measure based on a categorical-probabilistic approach. The results confirmed that assimilation complemented by the extrapolated data improves the accuracy of precipitation forecasts. The improvement was obvious in a majority of the single forecasts studied, and it is confirmed by all evaluation techniques. COSMO forecasts that used the extrapolation showed reasonable competence in forecasting for the first and the second hours. Copyright © 2011 Royal Meteorological Society

Description: This study assesses the variability of the amounts of annual precipitation in global land areas (excluding Greenland and Antarctica) from 1951 to 2000. The analysis is based on 0.5° longitude/latitude gridded data. Three different data sets were analysed (University of East Anglia Climate Research Unit's (UEA CRU) TS 2.1 data set, the Global Precipitation Climatology Centre's (GPCC) Full Data Reanalysis version 5 data set, Variability Analysis of Surface Climate Observations (VASClimO) version 1.1 data set), and all led to very similar results. The results included here correspond to the VasClimO project data. Precipitation variability is examined through the anomaly of the coefficient of variation, which is shown to be a robust concept. It is defined as the departure of the actual coefficient of variation from the value that could be expected ‘on average’, conditioned on the total annual amount of precipitation. A brief discussion of the so-called Jackknife error is included. The analysis revealed diverse areas of larger-than-normal, smaller-than-normal and close-to-normal variability. Negative anomalies occur more often but have, on an average, lower values than do positive anomalies. Large areas of slightly negative anomalies were found inland for all continents except Australia. A zonal pattern in the distribution of the anomalies was clearly seen at subtropical latitudes, which generally showed positive anomalies. This general picture is modified by various local factors, such as cold ocean currents, monsoon activity and cyclone formation areas. Global modes of climate variability, such as the El Niño-Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO), affect the variability of precipitation either directly or by modifying other relevant atmospheric and oceanic processes. Their influence is seen in many areas with higher-than-normal variability and is especially true if the high variability is accompanied by large amounts of mean annual precipitation. The authors believe that the present methodology may be useful in assessing the quality of future global data sets. It is, however, very desirable that such data sets include interpolation error estimates. Copyright © 2012 Royal Meteorological Society

Description: High-pressure spark plasma sintering (HPSPS) was employed to fabricate polycrystalline Nd:YAG specimens with desired functional properties. Specimens fabricated under a uniaxial pressure of 300 MPa at 1300°C at a heating rate of 50°C/min and holding time of 60 min displayed submicrometer microstructure and elevated mechanical properties, including resistance to thermal shock. Optical properties (i.e., spectral transmittance, fluorescence emission spectra and fluorescence lifetime) of the HPSPS-processed specimens were close to those obtained with specimens fabricated by conventional sintering procedure. Specifically, remarkable differences in threshold power and laser slope efficiency were found and attributed to the variance in Nd concentration in the specimens tested. The results of this study indicate that the low cost and timesaving HPSPS process allows for the fabrication of polycrystalline Nd:YAG specimens with optical properties suitable for laser applications.

Description: Two methods for assimilating radar reflectivity into the COSMO numerical weather prediction (NWP) model were compared to precipitation forecasts. The first method assimilated observed radar reflectivity, and the second one assimilated observed and extrapolated radar reflectivity. The assimilation technique was based on the correction of the model's water vapour mixing ratio. The extrapolation was performed by the COTREC method and was 1 hour long. The model's horizontal resolution was 2.8 km. The comparison of methods was based on verification of the observed and forecast hourly precipitation. The comparison was performed for the 1 st , 2 nd and 3 rd hours of each forecast. On the whole, 45 forecasts from nine days of convective precipitation were evaluated for each hour. The evaluation included subjective verification and the following objective skill scores: Fractions Skill Scores, SAL and a measure based on a categorical-probabilistic approach. The results confirmed that assimilation complemented by the extrapolated data improves the accuracy of precipitation forecasts. The improvement was obvious in a majority of the single forecasts studied, and it is confirmed by all evaluation techniques. COSMO forecasts that used the extrapolation showed reasonable competence in forecasting for the first and the second hours. Copyright © 2011 Royal Meteorological Society

Description: This study assesses the variability of the amounts of annual precipitation in global land areas (excluding Greenland and Antarctica) from 1951 to 2000. The analysis is based on 0.5° longitude/latitude gridded data. Three different data sets were analysed (University of East Anglia Climate Research Unit's (UEA CRU) TS 2.1 data set, the Global Precipitation Climatology Centre's (GPCC) Full Data Reanalysis version 5 data set, Variability Analysis of Surface Climate Observations (VASClimO) version 1.1 data set), and all led to very similar results. The results included here correspond to the VasClimO project data. Precipitation variability is examined through the anomaly of the coefficient of variation, which is shown to be a robust concept. It is defined as the departure of the actual coefficient of variation from the value that could be expected ‘on average’, conditioned on the total annual amount of precipitation. A brief discussion of the so-called Jackknife error is included. The analysis revealed diverse areas of larger-than-normal, smaller-than-normal and close-to-normal variability. Negative anomalies occur more often but have, on an average, lower values than do positive anomalies. Large areas of slightly negative anomalies were found inland for all continents except Australia. A zonal pattern in the distribution of the anomalies was clearly seen at subtropical latitudes, which generally showed positive anomalies. This general picture is modified by various local factors, such as cold ocean currents, monsoon activity and cyclone formation areas. Global modes of climate variability, such as the El Niño-Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO), affect the variability of precipitation either directly or by modifying other relevant atmospheric and oceanic processes. Their influence is seen in many areas with higher-than-normal variability and is especially true if the high variability is accompanied by large amounts of mean annual precipitation. The authors believe that the present methodology may be useful in assessing the quality of future global data sets. It is, however, very desirable that such data sets include interpolation error estimates. Copyright © 2012 Royal Meteorological Society

Description: We posit that how a plant carbon compound forms slow‐cycling mineral‐associated soil organic matter is tied to its point of entry to the mineral soil. In our spatially explicit conceptual model of soil organic matter formation, the microbial formation pathway is more dominant for belowground root inputs entering into the rhizosphere, whereas the direct sorption pathway is more dominant for aboveground dissolved organic matter inputs entering into the bulk soil. Due to these differences, the primacy of biotic vs. abiotic controls on soil organic matter formation will vary at fine spatial scales in soil space. Abstract To predict the behavior of the terrestrial carbon cycle, it is critical to understand the source, formation pathway, and chemical composition of soil organic matter (SOM). There is emerging consensus that slow‐cycling SOM generally consists of relatively low molecular weight organic carbon substrates that enter the mineral soil as dissolved organic matter and associate with mineral surfaces (referred to as “mineral‐associated OM,” or MAOM). However, much debate and contradictory evidence persist around: (a) whether the organic C substrates within the MAOM pool primarily originate from aboveground vs. belowground plant sources and (b) whether C substrates directly sorb to mineral surfaces or undergo microbial transformation prior to their incorporation into MAOM. Here, we attempt to reconcile disparate views on the formation of MAOM by proposing a spatially explicit set of processes that link plant C source with MAOM formation pathway. Specifically, because belowground vs. aboveground sources of plant C enter spatially distinct regions of the mineral soil, we propose that fine‐scale differences in microbial abundance should determine the probability of substrate–microbe vs. substrate–mineral interaction. Thus, formation of MAOM in areas of high microbial density (e.g., the rhizosphere and other microbial hotspots) should primarily occur through an in vivo microbial turnover pathway and favor C substrates that are first biosynthesized with high microbial carbon‐use efficiency prior to incorporation in the MAOM pool. In contrast, in areas of low microbial density (e.g., certain regions of the bulk soil), MAOM formation should primarily occur through the direct sorption of intact or partially oxidized plant compounds to uncolonized mineral surfaces, minimizing the importance of carbon‐use efficiency, and favoring C substrates with strong “sorptive affinity.” Through this framework, we thus describe how the primacy of biotic vs. abiotic controls on MAOM dynamics is not mutually exclusive, but rather spatially dictated. Such an understanding may be integral to more accurately modeling soil organic matter dynamics across different spatial scales.

Description: Soil organic matter is critical to sustainable agriculture because it provides nutrients to crops as it decomposes and increases nutrient- and water-holding capacity when built up. Fast- and slow-cycling fractions of soil organic matter can have different impacts on crop production because fast-cycling fractions rapidly release nutrients for short-term plant growth and slow-cycling fractions bind nutrients that mineralize slowly and build up water holding capacity. We explored the controls on these fractions in a tropical agroecosystem and their relationship to crop yields. We performed physical fractionation of soil organic matter from 48 farms and plots in western Kenya. We found that fast-cycling, particulate organic matter was positively related to crop yields, but did not have a strong effect, while slower-cycling, mineral-associated organic matter was negatively related to yields. Our finding that slower-cycling organic matter was negatively related to yield points to a need to revise the view that stabilization of organic matter positively impacts food security. Our results support a new paradigm that different soil organic matter fractions are controlled by different mechanisms, potentially leading to different relationships with management outcomes, like crop yield. Effectively managing soils for sustainable agriculture requires quantifying the effects of specific organic matter fractions on these outcomes. This article is protected by copyright. All rights reserved.

Description: [1]  Recently Sokół et al. (2012) have presented a reconstruction of heliolatitudinal and time variations of the solar wind speed and density. Method of the reconstruction was based on i) measurements of the interplanetary scintillations, ii) OMNI-2 solar wind data in the ecliptic plane, iii) Ulysses solar wind data out of the ecliptic plane. In this paper we use hydrogen charge exchange rates derived from their results as input parameters to calculate the interstellar hydrogen distribution in the heliosphere in the frame of our 3D time-dependent kinetic model. The hydrogen distribution is then used to calculate the backscattered solar Lyman-alpha intensity maps. The theoretical Lyman-alpha maps are compared with the SOHO/SWAN measurements during maximum and minimum of the solar cycle activity. We found that in the solar minimum there is a quite good agreement between the model results and the SWAN data, but in the solar maximum sky maps of the Lyman-alpha intensities are qualitatively different for the model results and observations. Physical reasons of the differences are discussed.